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Biomedical subjects

Xinhao Han

Publications and source records attributed to Xinhao Han.

2 recordsLinked to original sources

Oncotype DX-guided vs physician-directed chemotherapy and survival in HR+/HER2- breast cancer.

BACKGROUND: Oncotype DX testing guides adjuvant chemotherapy decisions in early-stage hormone receptor-positive/HER2-negative breast cancer, but testing is not universally performed, and outcomes associated with genomic-informed versus clinicopathologic-based chemotherapy decision pathways remain unclear. METHODS: Using the 2022 National Cancer Database Breast Participant User File, we identified women diagnosed from 2010 to 2022 with pathologic T1b-T2, node-negative, hormone receptor-positive/HER2-negative invasive breast cancer who received adjuvant chemotherapy and endocrine therapy. Patients were classified into an Oncotype-guided group, defined by Oncotype DX testing with a recurrence score of 26 or higher, and a physician-directed group, defined by receipt of chemotherapy without genomic testing. The primary outcome was overall survival. Analyses used multivariable Cox models, logistic-IPTW and MLP-IPTW, restricted mean survival time analysis, and a Bayesian latent confounding survival model. RESULTS: Among 56,625 women, 27,278 were in the Oncotype-guided group and 29,347 in the physician-directed group. Median ages were 59 and 56 years, respectively. The Oncotype-guided group had more favorable overall survival than the physician-directed group in multivariable Cox analysis (HR, 0.906; 95% CI, 0.856-0.959; P&#x202f;<&#x202f;0.001), with similar findings in IPTW analyses. The association was concentrated among patients aged 56 years or older (HR, 0.866; 95% CI, 0.809-0.927; P&#x202f;<&#x202f;0.001). The Bayesian model showed no strong residual confounding signal. CONCLUSIONS: Among chemotherapy-treated women, an Oncotype-guided pathway was associated with more favorable overall survival than a physician-directed pathway, particularly among older patients, which indicating prognostic heterogeneity selected using genomic versus conventional clinicopathologic information.

Humans

Identification of NR4A2 as a Potential Predictive Biomarker for Atherosclerosis.

INTRODUCTION/OBJECTIVE: Atherosclerosis, a leading cause of death globally, is characterized by the buildup of immune cells and lipids in medium to large-sized arteries. However, its precise mechanism remains unclear. The purpose of this study is to explore innovative and reliable biomarkers as a viable approach for the identification and management of atherosclerosis. METHODS: The atherosclerosis-related datasets GSE100927 and GSE66360 were retrieved from the Gene Expression Omnibus (GEO) database. The Limma package in the R programming language was utilized, applying the criteria of |logFC| > 1 and P < 0.05. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 127 identified DEGs using R. Machine learning techniques were then applied to these data to explore and pinpoint potential biomarkers. The diagnostic potential of these markers was assessed via Receiver Operating Characteristic (ROC) curve analysis. Finally, western blot, real-time quantitative PCR (qRT-PCR), and immunohistochemistry (IHC) were employed to confirm the key biomarkers. RESULTS: Our research indicated that a total of 127 DEGs linked to atherosclerosis were successfully identified. Through the application of machine learning methods, eight critical genes were highlighted. Among these, Nuclear Receptor Subfamily 4 Group A Member-2 (NR4A2) emerged as the most promising marker for further investigation. CIBERSORT analysis revealed that NR4A2 expression levels were significantly correlated with multiple immune cell types, including B cells, plasma cells, and macrophages. Additional validation experiments confirmed that NR4A2 expression was indeed elevated in atherosclerotic plaques, supporting its potential as a biomarker for atherosclerosis. CONCLUSION: Our study identified NR4A2 as a potential immune-related biomarker for the diagnosis and treatment of atherosclerosis.

Atherosclerosis